TY - GEN
T1 - GAN'SDA Wrap: Geographic And Network Structured DAta on surfaces that Wrap around
AU - Chen, Kun Ting
AU - Dwyer, Tim
AU - Yang, Yalong
AU - Bach, Benjamin
AU - Marriott, Kim
N1 - Funding Information:
We thank Bernhard Jenny, Lonni Besançon, Sarah Schöttler, Hong Gui, Mengxing Li, Ishwari Bhade, Umair Afzal, Sunny Singh for helpful discussion about the study design, anonymous participants for user study feedback, and our reviewers for helpful suggestions to improve this manuscript. We thank Stay Healthy and Monash eSolution crew for their technical support. This research is supported in part by Monash FIT Graduate Research Candidature Funding Scheme.
Publisher Copyright:
© 2022 ACM.
PY - 2022/4/28
Y1 - 2022/4/28
N2 - There are many methods for projecting spherical maps onto the plane. Interactive versions of these projections allow the user to centre the region of interest. However, the effects of such interaction have not previously been evaluated. In a study with 120 participants we find interaction provides significantly more accurate area, direction and distance estimation in such projections. The surface of 3D sphere and torus topologies provides a continuous surface for uninterrupted network layout. But how best to project spherical network layouts to 2D screens has not been studied, nor have such spherical network projections been compared to torus projections. Using the most successful interactive sphere projections from our first study, we compare spherical, standard and toroidal layouts of networks for cluster and path following tasks with 96 participants, finding benefits for both spherical and toroidal layouts over standard network layouts in terms of accuracy for cluster understanding tasks.
AB - There are many methods for projecting spherical maps onto the plane. Interactive versions of these projections allow the user to centre the region of interest. However, the effects of such interaction have not previously been evaluated. In a study with 120 participants we find interaction provides significantly more accurate area, direction and distance estimation in such projections. The surface of 3D sphere and torus topologies provides a continuous surface for uninterrupted network layout. But how best to project spherical network layouts to 2D screens has not been studied, nor have such spherical network projections been compared to torus projections. Using the most successful interactive sphere projections from our first study, we compare spherical, standard and toroidal layouts of networks for cluster and path following tasks with 96 participants, finding benefits for both spherical and toroidal layouts over standard network layouts in terms of accuracy for cluster understanding tasks.
KW - Crowdsourced study
KW - Geographic visualization
KW - Graph visualization
KW - Map projection
UR - http://www.scopus.com/inward/record.url?scp=85130564481&partnerID=8YFLogxK
U2 - 10.1145/3491102.3501928
DO - 10.1145/3491102.3501928
M3 - Conference contribution
AN - SCOPUS:85130564481
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery, Inc
T2 - 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022
Y2 - 30 April 2022 through 5 May 2022
ER -